Description

An exploration of workplace participation and earnings patterns for diverse women in US STEM professions that upends the myth that STEM work benefits women economically.

Seen as part economic driver, part social remedy, STEM work is commonly understood to benefit both the US economy and people—particularly women—from underrepresented groups. But what do diverse women find when they work in US STEM occupations? What do STEM jobs really deliver—and for whom? In Disparate Measures, Mary Armstrong and Susan Averett challenge the conventional wisdom that a diverse US STEM workforce will bring about economic abundance for the women who participate in it. Combining intersectionality theory and critical data theory with a feminist economic analysis, the authors explore how different groups of diverse women truly fare in US STEM professions.

Disparate Measures is centered on eight unique, in-depth case studies, each of which provides an in

Disparate Measures

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Hardback by Mary A. Armstrong

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An exploration of workplace participation and earnings patterns for diverse women in US STEM professions that upends the myth that... Read more

    Publisher: MIT Press
    Publication Date: 4/9/2024
    ISBN13: 9780262048866, 978-0262048866
    ISBN10: 0262048868

    Non Fiction , Business, Finance & Law

    Description

    An exploration of workplace participation and earnings patterns for diverse women in US STEM professions that upends the myth that STEM work benefits women economically.

    Seen as part economic driver, part social remedy, STEM work is commonly understood to benefit both the US economy and people—particularly women—from underrepresented groups. But what do diverse women find when they work in US STEM occupations? What do STEM jobs really deliver—and for whom? In Disparate Measures, Mary Armstrong and Susan Averett challenge the conventional wisdom that a diverse US STEM workforce will bring about economic abundance for the women who participate in it. Combining intersectionality theory and critical data theory with a feminist economic analysis, the authors explore how different groups of diverse women truly fare in US STEM professions.

    Disparate Measures is centered on eight unique, in-depth case studies, each of which provides an in

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